Automated detection of lung nodules using HOG technique with chest X-ray images

U. Raghavendra, Anjan Gudigar, Tejaswi N. Rao, Hamido Fujita, U. Rajendra Acharya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Lung disease is a growing disease and hence needs lot of attention. It is difficult to delineate the boundary of the lung when it is imaged through X-ray due to poor resolution. Hence, computer aided diagnosis (CAD) is preferred as it assists the radiologists in efficient diagnosis. In this work, a novel supervised classification technique is proposed using histogram of oriented gradient (HOG) and neighborhood preserving embedding (NPE). Our method is evaluated using 2000 chest X-ray images and can efficiently classify normal and abnormal classes with a promising performance of 97.95% accuracy, using support vector machine (SVM) classifier.

Original languageEnglish
Title of host publicationNew Trends in Intelligent Software Methodologies, Tools and Techniques - Proceedings of the 17th International Conference, SoMeT 2018
EditorsEnrique Herrera-Viedma, Hamido Fujita
PublisherIOS Press
Pages1018-1026
Number of pages9
ISBN (Electronic)9781614998990
DOIs
Publication statusPublished - 01-01-2018
Event17th International Conference on New Trends in Intelligent Software Methodology Tools and Techniques, SoMeT 2018 - Granada, Spain
Duration: 26-09-201828-09-2018

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume303
ISSN (Print)0922-6389

Conference

Conference17th International Conference on New Trends in Intelligent Software Methodology Tools and Techniques, SoMeT 2018
Country/TerritorySpain
CityGranada
Period26-09-1828-09-18

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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